Databases and data stores, such as those containing data relating to materials, products, services, and the like, may include a plurality of data records (or files), with each record including multiple fields, and with each field containing data for a particular type of data associated with the record. For example, a data record for a particular replacement component of a machine may include fields for the name of the part, the part or “stock keeping unit” (SKU) number for the part, a text description of the part, one or more still images of the part, audio and/or video associated with the part (e.g., video showing installation of the part in the machine), and so on. Moreover, a record may contain more than one version of a field (e.g., multiple description fields for different languages, multiple video fields for different video formats, etc.). Consequently, the size of the various types of data fields of each record may vary widely, such as from a few bytes to several megabytes, possibly representing several different data formats.
As a result of the widely different sizes of data fields within a data record, as well as the potentially large overall size of each record, storage and synchronization of a data record for access by multiple applications may be difficult, complicated, and inefficient, as each application typically stores a copy of the complete record in a data store specifically associated with the application (e.g., a memory-based database, a Hadoop® Distributed File System (HDFS), a cloud storage service, or one or more hard disk devices or other data storage devices). Moreover, each update to a field (especially a large field) at a data source for the record may require the application to retrieve the new version of the field from that data source, thus increasing overall communication network traffic between the data source and the data stores of the various applications accessing those records.